Project Summary/Abstract Findings from several studies conducted in sub-Saharan Africa (SSA) suggest that adults in the region have higher prevalence of depression than their counterparts in many middle- and high-income countries. The Global Burden of Disease Study estimated that mental and substance use disorders account for 19% of disability years in sub-Saharan Africa and the South African Stress and Health study ? conducted in 2003-2004 as part of the World Health Organization's World Mental Health Survey Initiative ? found a lifetime and 12- month prevalence of mental disorders of 30.3% and 16.5%, respectively. Despite the high prevalence, however, little is known about the determinants as well as the dynamics of mental health outcomes in the region. Prior research in SSA has largely relied on a few cross-sectional datasets and focused on the association between mental health and a limited set of demographic characteristics. While studies outside SSA have utilized longitudinal data to examine how economic crises, natural disasters, and other stressful life events (SLEs) influence mental health outcomes, there has been little to no research on such effects in SSA despite the twin significance of disease- and accident-related mortality and mental disorders in the region. The proposed project will fill this important gap by utilizing data from the first nationally representative longitudinal survey of the South African population, the National Income Dynamics Study (NIDS). The NIDS data span a 7- year period (2008-2015), contain detailed information on mortality and other SLEs within households, and include measures of depressive symptoms for all adult household members. Aim 1 of the project is to explore and assess trends in mental health in South Africa over a 7-year period, including transitions into or out of poor mental health and the role of individual, household, and community factors in explaining these transitions. Aim 2 of the project is to determine patterns in depression before and after the mortality of a household member as well as other positive and negative events occurring in the household. Analyses will use panel data regression techniques including models with individual fixed effects and time trends. The project will ultimately enhance our understanding of how mortality is influencing mental health outcomes in South Africa and help determine the level of need for mental health services as well as ways to improve the targeted provision of such services.